{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ef822909",
   "metadata": {},
   "source": [
    "# GraphRAG with Wikipedia and GPT OSS\n",
    "\n",
    "[txtai](https://github.com/neuml/txtai) is an all-in-one AI framework for semantic search, LLM orchestration and language model workflows.\n",
    "\n",
    "Retrieval Augmented Generation (RAG) is one of the most popular techniques in the AI space today. RAG takes a user request, retrieves the best matching content and then plugs that context into an LLM prompt to generate an answer. When otherwise not mentioned, most assume the context is generated using a vector database query. But there is no rule that says context can't be generated with other methods. It could be a simple web query, SQL query, text index search or other traditional search.\n",
    "\n",
    "We also often hear the term GraphRAG. GraphRAG means different things to different people. Here we're going to build an example that uses `txtai`, [wikipedia](https://huggingface.co/datasets/NeuML/wikipedia-20250620) and [gpt-oss](https://huggingface.co/openai/gpt-oss-20b) to research a specific topic with graphs. `txtai` has a built-in graph component that automatically generates a graph network over the data loaded into an embeddings database. We'll use a pre-built embeddings database hosted on the Hugging Face Hub, [txtai-wikipedia-slim](https://hf.co/neuml/txtai-wikipedia-slim)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af580b8a",
   "metadata": {},
   "source": [
    "# Install dependencies\n",
    "\n",
    "Install `txtai` and all dependencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36b1fd23",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "!pip install git+https://github.com/neuml/txtai#egg=txtai[graph,pipeline-llm]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a3f8a01",
   "metadata": {},
   "source": [
    "# Load txtai-wikipedia-slim\n",
    "\n",
    "Next, we'll load the embeddings database. This database is the top 100K most viewed Wikipedia articles with both a dense vector index and graph network enabled."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "07b7dee4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from txtai import Embeddings\n",
    "\n",
    "embeddings = Embeddings().load(provider=\"huggingface-hub\", container=\"neuml/txtai-wikipedia-slim\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7255a293",
   "metadata": {},
   "source": [
    "# Build context with a graph query\n",
    "\n",
    "The `txtai` graph component supports the [openCypher](https://opencypher.org/) query language via the [GrandCypher](https://github.com/aplbrain/grand-cypher) library.\n",
    "\n",
    "openCypher is a language for expressive and efficient data querying of a property graph. In this example, we'll traverse the embeddings database graph looking for paths between nodes similar to `chatgpt` and `anthropic`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "37a7128f",
   "metadata": {},
   "outputs": [],
   "source": [
    "g = embeddings.search(\"\"\"\n",
    "MATCH P=(A)-[]->(B)\n",
    "WHERE SIMILAR(A, 'chatgpt') AND SIMILAR(B, 'anthropic')\n",
    "RETURN P\n",
    "LIMIT 10\n",
    "\"\"\", graph=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6848e16a",
   "metadata": {},
   "source": [
    "The query above is an extremely powerful combination of an vector similarity node search and a graph traversal query that walks the paths between nodes. It's much more expressive than simply saying find nodes similar to each of the concepts independently. It can be considered a `deep graph search`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9632d541",
   "metadata": {},
   "source": [
    "# Plot the context network\n",
    "\n",
    "Let's show the context as a graph plot!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3861f5b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import networkx as nx\n",
    "\n",
    "def plot(graph):\n",
    "    labels = {x: f\"{graph.attribute(x, 'id')}\" for x in graph.scan()}\n",
    "    colors = [\"#D32F2F\", \"#0277bd\", \"#7e57c2\", \"#757575\"]\n",
    "\n",
    "    results = embeddings.batchsimilarity(labels.values(), [\"Anthropic Claude\", \"Google Gemini\", \"OpenAI GPT\"])\n",
    "    colors = [colors[x[0][0]] for x in results]\n",
    "\n",
    "    options = {\n",
    "        \"node_size\": 1000,\n",
    "        \"node_color\": colors,\n",
    "        \"edge_color\": \"#454545\",\n",
    "        \"font_color\": \"#efefef\",\n",
    "        \"font_size\": 10,\n",
    "        \"alpha\": 1.0,\n",
    "    }\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(20, 9))\n",
    "    pos = nx.spring_layout(graph.backend, seed=0, k=0.9, iterations=50)\n",
    "    nx.draw_networkx(graph.backend, pos=pos, labels=labels, **options)\n",
    "    ax.set_facecolor(\"#303030\")\n",
    "    ax.axis(\"off\")\n",
    "    fig.set_facecolor(\"#303030\")\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "plot(g)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4344faab",
   "metadata": {},
   "source": [
    "# Print the context as text\n",
    "\n",
    "Let's further inspect the graph nodes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "947ca6f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "context = \"\"\n",
    "for x in g.scan():\n",
    "    uid = g.attribute(x, \"id\")\n",
    "\n",
    "    context += f\"- id: {uid}\\n\"\n",
    "    context += f\"  url: https://en.wikipedia.org/wiki/{uid.replace(' ', '_')}\\n\"\n",
    "    context += f\"  text: {g.attribute(x, 'text')}\\n\"\n",
    "    context += f\"  links: {[g.attribute(n, 'id') for n in g.edges(x)]}\\n\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "0d784fcd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "- id: ChatGPT\n",
      "  url: https://en.wikipedia.org/wiki/ChatGPT\n",
      "  text: ChatGPT is a generative artificial intelligence chatbot developed by OpenAI and released on November 30, 2022. It uses large language models (LLMs) such as GPT-4o as well as other multimodal models to create human-like responses in text, speech, and images. It has access to features such as searching the web, using apps, and running programs. It is credited with accelerating the AI boom, an ongoing period of rapid investment in and public attention to the field of artificial intelligence (AI). Some observers have raised concern about the potential of ChatGPT and similar programs to displace human intelligence, enable plagiarism, or fuel misinformation.\n",
      "  links: ['GPT-4', 'GPT-4.5', 'OpenAI', 'Gemini (chatbot)', 'GPT-3', 'GPT-4.1', 'Gemini (language model)', 'Anthropic', 'Claude (language model)']\n",
      "- id: GPT-4\n",
      "  url: https://en.wikipedia.org/wiki/GPT-4\n",
      "  text: Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model trained and created by OpenAI and the fourth in its series of GPT foundation models. It was launched on March 14, 2023, and made publicly available via the paid chatbot product ChatGPT Plus until being replaced in 2025, via OpenAI's API, and via the free chatbot Microsoft Copilot.\n",
      "  links: ['ChatGPT', 'GPT-3', 'GPT-4.5', 'GPT-4.1', 'OpenAI', 'Gemini (chatbot)', 'Gemini (language model)', 'Claude (language model)']\n",
      "- id: GPT-4.5\n",
      "  url: https://en.wikipedia.org/wiki/GPT-4.5\n",
      "  text: GPT-4.5 (codenamed \"Orion\") is a large language model developed by OpenAI as part of the GPT series. Officially released on February 27, 2025, GPT-4.5 is available to users subscribed to the ChatGPT Plus and Pro plans across web, mobile, and desktop platforms. Access is also provided through the OpenAI API and the OpenAI Developer Playground, but the company plans to phase out API access to the model in July.\n",
      "  links: ['GPT-4.1', 'GPT-4', 'ChatGPT', 'GPT-3', 'OpenAI', 'Claude (language model)', 'Gemini (language model)', 'Anthropic', 'Gemini (chatbot)']\n",
      "- id: OpenAI\n",
      "  url: https://en.wikipedia.org/wiki/OpenAI\n",
      "  text: OpenAI, Inc. is an American artificial intelligence (AI) organization founded in December 2015 and headquartered in San Francisco, California. It aims to develop \"safe and beneficial\" artificial general intelligence (AGI), which it defines as \"highly autonomous systems that outperform humans at most economically valuable work\". As a leading organization in the ongoing AI boom, OpenAI is known for the GPT family of large language models, the DALL-E series of text-to-image models, and a text-to-video model named Sora. Its release of ChatGPT in November 2022 has been credited with catalyzing widespread interest in generative AI.\n",
      "  links: ['ChatGPT', 'GPT-4', 'GPT-3', 'GPT-4.5', 'Anthropic', 'GPT-4.1', 'Gemini (chatbot)', 'Gemini (language model)']\n",
      "- id: Gemini (chatbot)\n",
      "  url: https://en.wikipedia.org/wiki/Gemini_(chatbot)\n",
      "  text: Gemini, formerly known as Bard, is a generative artificial intelligence chatbot developed by Google. Based on the large language model (LLM) of the same name, it was launched in 2023 in response to the rise of OpenAI's ChatGPT. It was previously based on the LaMDA and PaLM LLMs.\n",
      "  links: ['Gemini (language model)', 'ChatGPT', 'GPT-4', 'Anthropic', 'OpenAI', 'GPT-4.5']\n",
      "- id: GPT-3\n",
      "  url: https://en.wikipedia.org/wiki/GPT-3\n",
      "  text: Generative Pre-trained Transformer 3 (GPT-3) is a large language model released by OpenAI in 2020.\n",
      "  links: ['GPT-4', 'GPT-4.1', 'ChatGPT', 'OpenAI', 'GPT-4.5', 'Claude (language model)', 'Gemini (language model)']\n",
      "- id: GPT-4.1\n",
      "  url: https://en.wikipedia.org/wiki/GPT-4.1\n",
      "  text: GPT-4.1 is a large language model within OpenAI's GPT series. It was released on April 14, 2025. GPT-4.1 can be accessed through the OpenAI API or the OpenAI Developer Playground. Three different models were simultaneously released: GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano.\n",
      "  links: ['GPT-4.5', 'GPT-4', 'GPT-3', 'ChatGPT', 'OpenAI', 'Gemini (language model)', 'Claude (language model)']\n",
      "- id: Gemini (language model)\n",
      "  url: https://en.wikipedia.org/wiki/Gemini_(language_model)\n",
      "  text: Gemini is a family of multimodal large language models (LLMs) developed by Google DeepMind, and the successor to LaMDA and PaLM 2. Comprising Gemini Ultra, Gemini Pro, Gemini Flash, and Gemini Nano, it was announced on December 6, 2023, positioned as a competitor to OpenAI's GPT-4. It powers the chatbot of the same name. In March 2025, Gemini 2.5 Pro Experimental was rated as highly competitive.\n",
      "  links: ['Gemini (chatbot)', 'GPT-4', 'ChatGPT', 'GPT-4.5', 'GPT-4.1', 'GPT-3', 'OpenAI', 'Anthropic']\n",
      "- id: Anthropic\n",
      "  url: https://en.wikipedia.org/wiki/Anthropic\n",
      "  text: Anthropic PBC is an American artificial intelligence (AI) startup company founded in 2021. Anthropic has developed a family of large language models (LLMs) named Claude as a competitor to OpenAI's ChatGPT and Google's Gemini. According to the company, it researches and develops AI to \"study their safety properties at the technological frontier\" and use this research to deploy safe models for the public.\n",
      "  links: ['Claude (language model)', 'OpenAI', 'ChatGPT', 'Gemini (chatbot)', 'GPT-4.5', 'Gemini (language model)']\n",
      "- id: Claude (language model)\n",
      "  url: https://en.wikipedia.org/wiki/Claude_(language_model)\n",
      "  text: Claude is a family of large language models developed by Anthropic. The first model was released in March 2023.\n",
      "  links: ['Anthropic', 'GPT-3', 'GPT-4.5', 'GPT-4', 'ChatGPT', 'GPT-4.1']\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(context)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e0fa70a",
   "metadata": {},
   "source": [
    "# GraphRAG\n",
    "\n",
    "Now that we have our graph context, we'll plug that into an LLM prompt."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1465b3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from txtai import LLM\n",
    "\n",
    "llm = LLM(\"unsloth/gpt-oss-20b-GGUF/gpt-oss-20b-Q4_K_M.gguf\", n_ctx=20000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "74b4692c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "**ChatGPT, GPT‑4, and the New Generation of Generative AI: A Timeline of Innovation and Impact**\n",
       "\n",
       "*By [Your Name]*  \n",
       "*Published: 2025‑09‑03*\n",
       "\n",
       "---\n",
       "\n",
       "### 1.  The Dawn of Generative AI\n",
       "\n",
       "The field of artificial intelligence (AI) has long promised “highly autonomous systems that outperform humans at most economically valuable work.”  In practice, the most visible manifestation of that promise has been the rapid rise of large language models (LLMs) that can generate text, speech, and even images that read like they were written by a human.  The most influential of these models has come from a handful of companies—OpenAI, Google DeepMind, and Anthropic—each building a family of models that have pushed the boundaries of what machines can do.\n",
       "\n",
       "---\n",
       "\n",
       "### 2.  OpenAI’s GPT Series\n",
       "\n",
       "| Model | Release | Key Features | Notes |\n",
       "|-------|---------|---------------|-------|\n",
       "| **GPT‑3** | 2020 | 175 billion parameters; first public GPT model | Laid the groundwork for conversational AI |\n",
       "| **ChatGPT** | 2022‑11‑30 | Uses GPT‑4o and multimodal models; web‑search, app‑integration, program execution | Sparked the “AI boom” and widespread public interest |\n",
       "| **GPT‑4** | 2023‑03‑14 | Multimodal; released via ChatGPT Plus, API, Microsoft Copilot | Became the de‑facto standard for LLM‑based chat |\n",
       "| **GPT‑4.1** | 2025‑04‑14 | Three variants (mini, nano) released simultaneously | Improved safety and performance |\n",
       "| **GPT‑4.5** | 2025‑02‑27 | Codename “Orion”; API access to be phased out in July | Highest‑performance model in the GPT line |\n",
       "\n",
       "OpenAI’s mission—“safe and beneficial” artificial general intelligence—has guided the evolution of these models.  The company’s public releases have been accompanied by a steady stream of research papers, API documentation, and developer playgrounds that allow researchers and businesses to experiment with the models at scale.\n",
       "\n",
       "---\n",
       "\n",
       "### 3.  Google DeepMind’s Gemini\n",
       "\n",
       "Google’s response to the GPT wave came in 2023 with **Gemini (chatbot)**, a generative AI chatbot that replaced the earlier Bard.  Gemini is powered by the **Gemini (language model)** family, which includes Gemini Ultra, Pro, Flash, and Nano.  The models were announced on 2023‑12‑06 and positioned as direct competitors to GPT‑4.  In March 2025, Gemini 2.5 Pro Experimental was rated as “highly competitive,” underscoring the rapid parity between the two ecosystems.\n",
       "\n",
       "---\n",
       "\n",
       "### 4.  Anthropic’s Claude\n",
       "\n",
       "Founded in 2021, **Anthropic PBC** has focused on the safety properties of AI.  Their flagship LLM family, **Claude**, was first released in March 2023.  Claude is marketed as a competitor to both ChatGPT and Gemini, with a particular emphasis on “safe models for the public.”  Anthropic’s research agenda—studying safety at the technological frontier—has positioned it as a counter‑balance to the commercial focus of OpenAI and Google.\n",
       "\n",
       "---\n",
       "\n",
       "### 5.  The Feature Set that Changed the Game\n",
       "\n",
       "ChatGPT’s launch was not just a new model; it was a new **feature set**:\n",
       "\n",
       "* **Web Search** – The ability to query up‑to‑date information in real time.  \n",
       "* **App Integration** – Running third‑party applications directly from the chat interface.  \n",
       "* **Program Execution** – The capacity to run code snippets and return results.  \n",
       "\n",
       "These capabilities turned a simple chatbot into a *digital assistant* that can browse, compute, and even generate images (via DALL‑E) or video (via Sora).  The result was a surge in both consumer and enterprise adoption.\n",
       "\n",
       "---\n",
       "\n",
       "### 6.  Societal Impact and Concerns\n",
       "\n",
       "The rapid adoption of generative AI has accelerated the **AI boom**—a period of intense investment and public attention.  Yet it has also raised legitimate concerns:\n",
       "\n",
       "* **Displacement of Human Intelligence** – Critics worry that advanced LLMs could replace human expertise in fields ranging from journalism to law.  \n",
       "* **Plagiarism and Academic Integrity** – The ease of producing high‑quality text has made it harder to detect original work.  \n",
       "* **Misinformation** – Models can generate plausible but false narratives, amplifying the spread of fake news.  \n",
       "\n",
       "OpenAI, Google, and Anthropic have all invested in safety research, but the debate continues over how best to balance innovation with responsibility.\n",
       "\n",
       "---\n",
       "\n",
       "### 7.  Looking Ahead\n",
       "\n",
       "The trajectory of generative AI suggests a few key trends:\n",
       "\n",
       "1. **Continued Model Scaling** – GPT‑4.5 and GPT‑4.1 demonstrate that larger models still deliver incremental gains.  \n",
       "2. **Multimodal Integration** – Future releases will likely blend text, image, audio, and video more tightly.  \n",
       "3. **Regulatory Engagement** – Governments and industry groups are beginning to draft guidelines for AI safety and transparency.  \n",
       "4. **Democratization of Access** – APIs and developer playgrounds are making advanced AI available to a broader audience, from hobbyists to large enterprises.  \n",
       "\n",
       "---\n",
       "\n",
       "### 8.  Conclusion\n",
       "\n",
       "From GPT‑3’s 175 billion parameters to GPT‑4.5’s “Orion” codename, the generative AI landscape has evolved at a breakneck pace.  OpenAI’s ChatGPT catalyzed a wave of public fascination, while Google’s Gemini and Anthropic’s Claude have kept the competition fierce.  As these models become more capable, the conversation around safety, ethics, and societal impact will only grow more urgent.  The next few years will likely see generative AI move from a novelty to a foundational technology—one that will shape how we write, compute, and even think.\n",
       "\n",
       "---\n",
       "\n",
       "**References**\n",
       "\n",
       "* ChatGPT – https://en.wikipedia.org/wiki/ChatGPT  \n",
       "* GPT‑4 – https://en.wikipedia.org/wiki/GPT-4  \n",
       "* GPT‑4.5 – https://en.wikipedia.org/wiki/GPT-4.5  \n",
       "* OpenAI – https://en.wikipedia.org/wiki/OpenAI  \n",
       "* Gemini (chatbot) – https://en.wikipedia.org/wiki/Gemini_(chatbot)  \n",
       "* GPT‑3 – https://en.wikipedia.org/wiki/GPT-3  \n",
       "* GPT‑4.1 – https://en.wikipedia.org/wiki/GPT-4.1  \n",
       "* Gemini (language model) – https://en.wikipedia.org/wiki/Gemini_(language_model)  \n",
       "* Anthropic – https://en.wikipedia.org/wiki/Anthropic  \n",
       "* Claude (language model) – https://en.wikipedia.org/wiki/Claude_(language_model)  \n",
       "\n",
       "---"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import display, Markdown\n",
    "\n",
    "out = llm(f\"\"\"\n",
    "Analyze the following context and write an article about it\n",
    "{context}\n",
    "\"\"\", defaultrole=\"user\", maxlength=20000, stripthink=True)\n",
    "\n",
    "display(Markdown(out))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ecf44b7",
   "metadata": {},
   "source": [
    "# Wrapping up\n",
    "\n",
    "There we have it, GraphRAG in a very straightforward and easy-to-understand manner. The best ideas often are the simple ones!\n",
    "\n"
   ]
  }
 ],
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 },
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